4 citations · 6 across the 6 of their papers we have counts for
6 papers
Learning interpretable surface elasticity properties from bulk properties
Saaketh Desai, Prasad P. Iyer, Remi Dingreville
Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface s…
Equilibrium Conserving Neural Operators for Super-Resolution Learning
Vivek Oommen, Andreas E. Robertson, Daniel Diaz +5
Neural surrogate solvers can estimate solutions to partial differential equations in physical problems more efficiently than standard numerical methods, but require extensive high-…
AutoSciLab: A Self-Driving Laboratory For Interpretable Scientific Discovery
Saaketh Desai, Sadhvikas Addamane, Jeffrey Y. Tsao +4
Advances in robotic control and sensing have propelled the rise of automated scientific laboratories capable of high-throughput experiments. However, automated scientific laborator…
Micropolar elastoplasticity using a fast Fourier transform-based solver
Noah M. Francis, Ricardo A. Lebensohn, Fatemeh Pourahmadian +1
This work presents a micromechanical spectral formulation for obtaining the full-field and homogenized response of elastoplastic micropolar composites. A closed-form radial-return…
Self-driving lab discovers principles for steering spontaneous emission
Saaketh Desai, Sadhvikas Addamane, Jeffery Y. Tsao +3
We developed an autonomous experimentation platform to accelerate interpretable scientific discovery in ultrafast nanophotonics, targeting a novel method to steer spontaneous emiss…
Rethinking materials simulations: Blending direct numerical simulations with neural operators
Vivek Oommen, Khemraj Shukla, Saaketh Desai +2
Direct numerical simulations (DNS) are accurate but computationally expensive for predicting materials evolution across timescales, due to the complexity of the underlying evolutio…